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Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting label errors and increasing overall dataset quality. It implements a confident learning framework that iteratively refines label noise estimates by comparing model predictions with estimated label probabilities to identify mislabeled examples. The project provides specialized utilities for active learning optimization, allowing for the selection of the most impactful examples for labeling or re-labeling. It also includes an outlier detection tool to identify atypical data poin
Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/
Jupytext is a synchronization tool and text converter for Jupyter Notebooks. It transforms notebook files into plain text formats, such as Markdown or Python scripts, to enable line-by-line diffs and peer reviews within version control systems. The tool pairs notebook files with corresponding text files to maintain a dual representation of the same content. It uses bidirectional synchronization to update linked files based on the most recent modifications, allowing notebook content to be edited inside standard text editors. Beyond file conversion and synchronization, the project provides cap
Snorkel is a weak supervision system that enables users to programmatically generate training labels for machine learning models without manual annotation. At its core, it provides a framework for writing labeling functions as Python callables that each vote on data points, and then trains a probabilistic graphical model over these multiple weak supervision sources to estimate latent true labels without any ground truth data. The system automatically learns accuracy and correlation parameters between labeling functions by analyzing observed agreement patterns on unlabeled data, converting lab
Open-source low code data preparation library in python. Collect, clean and visualization your data in python with a few lines of code.
The main features of sfu-db/dataprep are: Data Centric AI, Data Exploration.
Projects with overlapping indexed features include: cleanlab/cleanlab — Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting… deepnote/deepnote — Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data… mwouts/jupytext — Jupytext is a synchronization tool and text converter for Jupyter Notebooks. It transforms notebook files into plain… snorkel-team/snorkel — Snorkel is a weak supervision system that enables users to programmatically generate training labels for machine… tkrabel/bamboolib — bamboolib - a GUI for pandas DataFrames. ydataai/pandas-profiling — This project is an exploratory data analysis framework and profiling tool designed to generate comprehensive…